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An intraoperative visualization system using hyperspectral imaging to aid in brain tumor delineation

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Title: An intraoperative visualization system using hyperspectral imaging to aid in brain tumor delineation
Authors: Fabelo, H
Ortega, S
Lazcano, R
Madroñal, D
M Callicó, G
Juárez, E
Salvador, R
Bulters, D
Bulstrode, H
Szolna, A
Piñeiro, JF
Sosa, C
J O'Shanahan, A
Bisshopp, S
Hernández, M
Morera, J
Ravi, D
Kiran, BR
Vega, A
Báez-Quevedo, A
Yang, G-Z
Stanciulescu, B
Sarmiento, R
Item Type: Journal Article
Abstract: Hyperspectral imaging (HSI) allows for the acquisition of large numbers of spectral bands throughout the electromagnetic spectrum (within and beyond the visual range) with respect to the surface of scenes captured by sensors. Using this information and a set of complex classification algorithms, it is possible to determine which material or substance is located in each pixel. The work presented in this paper aims to exploit the characteristics of HSI to develop a demonstrator capable of delineating tumor tissue from brain tissue during neurosurgical operations. Improved delineation of tumor boundaries is expected to improve the results of surgery. The developed demonstrator is composed of two hyperspectral cameras covering a spectral range of 400-1700 nm. Furthermore, a hardware accelerator connected to a control unit is used to speed up the hyperspectral brain cancer detection algorithm to achieve processing during the time of surgery. A labeled dataset comprised of more than 300,000 spectral signatures is used as the training dataset for the supervised stage of the classification algorithm. In this preliminary study, thematic maps obtained from a validation database of seven hyperspectral images of in vivo brain tissue captured and processed during neurosurgical operations demonstrate that the system is able to discriminate between normal and tumor tissue in the brain. The results can be provided during the surgical procedure (~1 min), making it a practical system for neurosurgeons to use in the near future to improve excision and potentially improve patient outcomes.
Issue Date: 1-Feb-2018
Date of Acceptance: 30-Jan-2018
URI: http://hdl.handle.net/10044/1/58473
DOI: https://dx.doi.org/10.3390/s18020430
ISSN: 1424-2818
Publisher: MDPI AG
Journal / Book Title: Sensors (Basel, Switzerland)
Volume: 18
Issue: 2
Copyright Statement: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Keywords: brain cancer detection
hyperspectral imaging instrumentation
image processing
0301 Analytical Chemistry
0906 Electrical And Electronic Engineering
Analytical Chemistry
Publication Status: Published
Conference Place: Switzerland
Open Access location: http://www.mdpi.com/1424-8220/18/2/430
Article Number: ARTN 430
Appears in Collections:Computing